Profiling the mobile-only population in Australia: insights from the Australian National Health Survey
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Baffour-Awuah, Bernard; Haynes, Michele; Dinsdale, Shane; Western, Mark; Pennay, Darren
Description
Background: The Australian population that relies on mobile phones exclusively has increased from 5% in 2005 to 29% in 2014. Failing to include this mobile-only population leads to a potential bias in estimates from landline-based telephone surveys. This paper considers the impacts on selected health prevalence estimates with and without the mobile-only population. Methods: Using data from the Australian Health Survey – which, for the first time, included a question on telephone status – we...[Show more]
dc.contributor.author | Baffour-Awuah, Bernard | |
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dc.contributor.author | Haynes, Michele | |
dc.contributor.author | Dinsdale, Shane | |
dc.contributor.author | Western, Mark | |
dc.contributor.author | Pennay, Darren | |
dc.date.accessioned | 2018-11-29T22:54:54Z | |
dc.date.available | 2018-11-29T22:54:54Z | |
dc.identifier.issn | 1326-0200 | |
dc.identifier.uri | http://hdl.handle.net/1885/152965 | |
dc.description.abstract | Background: The Australian population that relies on mobile phones exclusively has increased from 5% in 2005 to 29% in 2014. Failing to include this mobile-only population leads to a potential bias in estimates from landline-based telephone surveys. This paper considers the impacts on selected health prevalence estimates with and without the mobile-only population. Methods: Using data from the Australian Health Survey – which, for the first time, included a question on telephone status – we examined demographic, geographic and health differences between the landline-accessible and mobile-only population. These groups were also compared to the full population, controlling for the sampling design and differential non-response patterns in the observed sample through weighting and benchmarking. Results: The landline-accessible population differs from the mobile-only population for selected health measures resulting in biased prevalence estimates for smoking, alcohol risk and private health insurance coverage in the full population. The differences remain even after adjusting for age and gender. Conclusions: Using landline telephones only for conducting population health surveys will have an impact on prevalence rate estimates of health risk factors due to the differing profiles of the mobile-only population from the landline-accessible population. | |
dc.format.mimetype | application/pdf | |
dc.publisher | Public Health Association of Australia | |
dc.source | Australian and New Zealand Journal of Public Health | |
dc.title | Profiling the mobile-only population in Australia: insights from the Australian National Health Survey | |
dc.type | Journal article | |
local.description.notes | Imported from ARIES | |
local.identifier.citationvolume | 40 | |
dc.date.issued | 2016 | |
local.identifier.absfor | 111104 - Public Nutrition Intervention | |
local.identifier.ariespublication | u4326120xPUB720 | |
local.type.status | Published Version | |
local.contributor.affiliation | Baffour-Awuah, Bernard, College of Arts and Social Sciences, ANU | |
local.contributor.affiliation | Haynes, Michele, University of Queensland | |
local.contributor.affiliation | Dinsdale, Shane, University of Queensland | |
local.contributor.affiliation | Western, Mark, University of Queensland | |
local.contributor.affiliation | Pennay, Darren, College of Arts and Social Sciences, ANU | |
local.bibliographicCitation.issue | 5 | |
local.bibliographicCitation.startpage | 443 | |
local.bibliographicCitation.lastpage | 447 | |
local.identifier.doi | 10.1111/1753-6405.12549 | |
dc.date.updated | 2018-11-29T08:03:17Z | |
local.identifier.scopusID | 2-s2.0-84989807052 | |
local.identifier.thomsonID | 000385669900008 | |
dcterms.accessRights | Open Access | |
Collections | ANU Research Publications |
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File | Description | Size | Format | Image |
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01_Baffour-Awuah_Profiling_the_mobile-only_2016.pdf | 110.99 kB | Adobe PDF | ![]() |
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